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Ratnesh Singh Thakur

from San Jose, CA
Age ~40
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Also known as:
Ratnesh S Thakur, H Thakur
Related to:
Ajay Kumar Singh, 44Nilesh S Thakur, 45Dinesh Singh Thakur, 39Aditya S Thakur, 35Sanjana Thakur, 41Ritesh S Thakur, 42
Connected to:
Ahmed S Thakur, 72Ajit V Thakur, 78Akanksha Thakur, 38Alpana K Thakur, 54Amita D Thakur, 59Angelica S Thakur, 81Anshuman Thakur, 43Apoorv Thakur, 42Bhupinder Thakur, 40Bidhan Thakur, 38

Ratnesh Thakur Phones & Addresses

  • San Jose, CA
  • Tracy, CA
  • Sunnyvale, CA

Publications

Us Patents

Adaptive Anomaly Detector

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US Patent:
20210350277, Nov 11, 2021
Filed:
Jun 19, 2020
Appl. No.:
16/906119
Inventors:
- Ft. Lauderdale FL, US
Josephine Suganthi Joseph Leo - Sunnyvale CA, US
Kasirao Velugu - Bangalore, IN
Praveen Dandin - Fremont CA, US
Rama Rao Katta - Fremont CA, US
Ratnesh Singh Thakur - San Jose CA, US
Seth Kenneth Keith - Scotts Valley CA, US
Rakesh Thangellapalli - Milpitas CA, US
International Classification:
G06N 20/00
G06N 3/04
G06N 3/08
H04L 29/06
Abstract:
A computer system is provided. The computer system includes a memory, a network interface, and a processor coupled to the memory and the network interface. The processor is configured to receive a response to a request to verify whether an ostensible client of a service is actually a client or a bot, the response including an indicator of whether the ostensible client is a client or a bot; receive information descriptive of interoperations between the ostensible client and the service that are indicative of whether the ostensible client is a client or a bot; and train a plurality of machine learning classifiers using the information and the indicator to generate a next generation of the plurality of machine learning classifiers.

Generating Urls To Detect Autonomous Programs Systems And Methods

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US Patent:
20210281605, Sep 9, 2021
Filed:
Mar 4, 2020
Appl. No.:
16/808731
Inventors:
- Fort Lauderdale FL, US
Rama Rao KATTA - Sunnyvale CA, US
Kasirao VELUGU - Bengaluru, IN
Praveen DANDIN - Santa Clara CA, US
Aman AGRAWAL - Bengaluru, IN
Seth Kenneth KEITH - Scotts Valley CA, US
Ratnesh SINGH THAKUR - San Jose CA, US
Josephine SUGANTHI JOSEPH LEO - Sunnyvale CA, US
International Classification:
H04L 29/06
G06F 16/955
Abstract:
Described embodiments provide systems and methods for detecting autonomous programs is provided. A device, intermediary to a plurality of clients and a plurality of servers, can receive a first request from a first client of the plurality of clients to a server of the plurality of servers via a connection between the device and the first client. The device can include, into a response from the server to the first client, a uniform resource locator (URL) comprising one or more randomly generated characters within a predetermined character space. The device can determine that the first client has an autonomous program responsive to receiving a second request from the first client using the URL. The device can terminate, responsive to the determination, the connection to the first client.

Feature Engineering For Web-Based Anomaly Detection

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US Patent:
20200067948, Feb 27, 2020
Filed:
Oct 28, 2019
Appl. No.:
16/666092
Inventors:
- Fort Lauderdale FL, US
Anoop Reddy - San Jose CA, US
Ratnesh Singh Thakur - Sunnyvale CA, US
International Classification:
H04L 29/06
Abstract:
The present disclosure is directed towards systems and methods for detecting anomalous network traffic. Network traffic corresponding to an application executed by a server can be received. Application characteristics of the application can be identified to select an anomaly detection profile. The anomaly detection profile can be selected based on the identified application characteristics. The anomaly detection profile can include a set of detection features for the anomaly and one or more predetermined threshold values of the detection features. One or more feature values of the set of one or more detection features can be determined. An anomaly in the network traffic can be detected responsive to comparing the feature values and the predetermined threshold values of the detection features.

Anomaly Detection With K-Means Clustering And Artificial Outlier Injection

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US Patent:
20170124478, May 4, 2017
Filed:
Oct 30, 2015
Appl. No.:
14/927553
Inventors:
- Fort Lauderdale FL, US
Anoop Reddy - San Jose CA, US
Ratnesh Singh Thakur - Sunnyvale CA, US
International Classification:
G06N 99/00
H04L 12/26
Abstract:
The present disclosure is directed towards systems and methods for improving anomaly detection using injected outliers. A normalcy calculator of a device may include a set of outliers into a training dataset of data points. The normalcy calculator, using a K-means clustering algorithm applied on the training dataset, identify at least a first cluster of data points. The normalcy calculator of the device may determine a region with a center and an outer radius that covers at least a spatial extent of the first cluster of data points. The normalcy calculator may determine a first normalcy radius for the first cluster by reducing the region around the center until a point at which all artificial outliers are excluded from a region defined by the first normalcy radius. An outlier detector of the device may use the region defined by the first normalcy radius to determine whether a new data point is normal or abnormal.

Feature Engineering For Web-Based Anomaly Detection

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US Patent:
20170126709, May 4, 2017
Filed:
Oct 30, 2015
Appl. No.:
14/927580
Inventors:
- Fort Lauderdale FL, US
Anoop Reddy - San Jose CA, US
Ratnesh Singh Thakur - Sunnyvale CA, US
International Classification:
H04L 29/06
Abstract:
The present disclosure is directed towards systems and methods for detecting anomalous network traffic. Network traffic corresponding to an application executed by a server can be received. Application characteristics of the application can be identified to select an anomaly detection profile. The anomaly detection profile can be selected based on the identified application characteristics. The anomaly detection profile can include a set of detection features for the anomaly and one or more predetermined threshold values of the detection features. One or more feature values of the set of one or more detection features can be determined. An anomaly in the network traffic can be detected responsive to comparing the feature values and the predetermined threshold values of the detection features.

Framework For Explaining Anomalies In Accessing Web Applications

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US Patent:
20170126718, May 4, 2017
Filed:
Oct 30, 2015
Appl. No.:
14/928217
Inventors:
- Fort Lauderdale FL, US
Anoop Reddy - San Jose CA, US
Ratnesh Singh Thakur - Sunnyvale CA, US
International Classification:
H04L 29/06
Abstract:
The present disclosure is directed towards systems and methods for characterizing anomalous network traffic. The system includes a device intermediary to clients and servers. The device includes a network traffic engine to receive network traffic including an anomaly. The device includes a univariate policy manager to determine whether the network traffic satisfies at least one of the rules of a univariate policy based on a respective single independent network traffic feature. The device includes a multivariate policy manager to determine, responsive to determining that the network traffic does not satisfy the rules of the univariate policy, that the network satisfies a multivariate policy including a plurality of anomaly explanation tests. The device includes an anomaly explanation selector to select, responsive to determining that the network traffic satisfies the multivariate policy, an anomaly explanation. The device includes a message generator to generate an anomaly explanation output including the selected anomaly explanation.

Protect Applications From Session Stealing/Hijacking Attacks By Tracking And Blocking Anomalies In End Point Characteristics Throughout A User Session

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US Patent:
20150341383, Nov 26, 2015
Filed:
May 23, 2014
Appl. No.:
14/286610
Inventors:
- Fort Lauderdale FL, US
Rama Rao Katta - Bangalore, IN
Bhanu Prakash Valluri - Bangalore, IN
Craig Anderson - Sunnyvale CA, US
Ratnesh Singh Thakur - Sunnyvale CA, US
Assignee:
Citrix Systems, Inc. - Fort Lauderdale FL
International Classification:
H04L 29/06
H04L 29/08
Abstract:
Systems and methods for protection against session stealing is described. In embodiments of the present solution, a device intermediary to the client and the server may identify first properties of the client and associate the first properties with the session key. When the device receives subsequent request comprising the session key, the device matches the associated first properties with second properties of the second device that is sending the subsequent request. If there is a match, the subsequent request transmitted to the server. Otherwise, the subsequent request is rejected.
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Ratnesh Singh Thakur from San Jose, CA, age ~40 Get Report